The ability to present three-dimensional (3D) scenes with continuous depth sensation has a profound impact on virtual and augmented reality, human-computer interaction, education and training. Computer-generated holography (CGH) enables high-spatio-a...
Neural networks : the official journal of the International Neural Network Society
Mar 4, 2021
With the increasing demand of mining rich knowledge in graph structured data, graph embedding has become one of the most popular research topics in both academic and industrial communities due to its powerful capability in learning effective represen...
Reasoning about graphs evolving over time is a challenging concept in many domains, such as bioinformatics, physics, and social networks. We consider a common case in which edges can be short term interactions (e.g., messaging) or long term structura...
IEEE transactions on visualization and computer graphics
Feb 1, 2021
Deep learning's great success motivates many practitioners and students to learn about this exciting technology. However, it is often challenging for beginners to take their first step due to the complexity of understanding and applying deep learning...
IEEE transactions on visualization and computer graphics
Jan 28, 2021
Convolutional neural networks (CNNs) have demonstrated extraordinarily good performance in many computer vision tasks. The increasing size of CNN models, however, prevents them from being widely deployed to devices with limited computational resource...
IEEE transactions on visualization and computer graphics
Jan 28, 2021
Shaded relief is an effective method for visualising terrain on topographic maps, especially when the direction of illumination is adapted locally to emphasise individual terrain features. However, digital shading algorithms are unable to fully match...
IEEE transactions on visualization and computer graphics
Jan 28, 2021
Investigating relationships between variables in multi-dimensional data sets is a common task for data analysts and engineers. More specifically, it is often valuable to understand which ranges of which input variables lead to particular values of a ...
IEEE transactions on visualization and computer graphics
Jan 28, 2021
To mitigate the pain of manually tuning hyperparameters of deep neural networks, automated machine learning (AutoML) methods have been developed to search for an optimal set of hyperparameters in large combinatorial search spaces. However, the search...
IEEE transactions on visualization and computer graphics
Jan 28, 2021
The fundamental motivation of the proposed work is to present a new visualization-guided computing paradigm to combine direct 3D volume processing and volume rendered clues for effective 3D exploration. For example, extracting and visualizing microst...
IEEE transactions on visualization and computer graphics
Jan 28, 2021
In recent years, deep learning has opened countless research opportunities across many different disciplines. At present, visualization is mainly applied to explore and explain neural networks. Its counterpart-the application of deep learning to visu...
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